Modelagem de energia fotovoltaica em função de parâmetros climáticos

  1. Amaury Souza 1
  2. Ana Paula Garcia Oliveira 2
  3. Ataur Rahman 3
  4. Mahmudul Haque 3
  1. 1 Universidade Federal de Mato Grosso do Sul
    info

    Universidade Federal de Mato Grosso do Sul

    Campo Grande, Brasil

    ROR https://ror.org/0366d2847

  2. 2 Universidade Anhanguera-Uniderp
    info

    Universidade Anhanguera-Uniderp

    Campo Grande, Brasil

    ROR https://ror.org/00hbwk525

  3. 3 University of Western Sydney
    info

    University of Western Sydney

    Richmond, Australia

    ROR https://ror.org/03t52dk35

Mostrar afiliacións +
Revista:
Revista Geociências

ISSN: 1981-741X

Ano de publicación: 2019

Volume: 18

Número: 1

Páxinas: 31-41

Tipo: Artigo

DOI: 10.33947/1981-7428-V18N1-2916 DIALNET GOOGLE SCHOLAR lock_openAcceso aberto editor

Outras publicacións en: Revista Geociências

Resumo

Photovoltaic energy productivity (PVE) is evaluated using simulated climatic variables with aerosol, clarity index and solar irradiance and a model for the performance of photovoltaic systems. The analysis indicates that the aerosol emission reductions in the near future result in an increase in global warming and a significant response of the solar surface radiation and associated PVE productivity. Changes in radiation surface and productivity of solar PVE are related to overall reduction aerosol effects on the circulation and large scale associated with cloud coverage pattern, rather than local atmospheric effects on optical properties. PVE evaluation is then discussed in the context of the current situation and the PV market, highlighting the effects on productivity induced by industrial and public policies, and technological development are comparable to the effects related to the weather. The results presented encourage the improvement and further use of climate models in the assessment of future availability for renewable energy

Referencias bibliográficas

  • ALBRECHT, B. A. Aerosols, cloud microphysics, and fractional cloudiness. Science, 245, 1989, 1227– 1230 p.
  • ANGSTROEM, A. Atmospheric turbidity, global illumination and planetary albedo of the earth. Tellus, 14, 1962, 435–450p.
  • ARTAXO, P.; OLIVEIRA, P. H.; LARA, L. L.; PAULIQUEVIS, T. M.; RIZZO, L. V.; PIRES JUNIOR, C.; PAIXÃO, M. A; LONGO K. M., DE FREITAS, S; CORREIA, A. L. Efeitos Climáticos de Partículas de Aerossóis Biogênicos e Emitidos em Queimadas na Amazônia. Revista Brasileira de Meteorologia, v.21, n.3, 2006,168-22p.
  • BRASSEUR, G.; PRINN, R. G.; Pszenny, A. A. P. Atmospheric chemistry in a changing world, an integration and synthesis of a decade of tropospheric chemistry research, Springer, Berlin, 2003, 125–156p.
  • DELUCCHI, M. A.; JACOBSON, M. Z. Providing all global energy with wind, water, and solar power, Part II: reliability, system and transmission costs, and policies. Energy Policy, 39, 2011, 1170–1190p.
  • DENHOLM, P.; HAND, M. Grid flexibility and storage required to achieve very high penetration of variable renewable electricity. Energy Policy, 39, 2011, 1817–1830p.
  • DE SOUZA, A.; ARISTONE, F.; SABBAH, I. Modeling the Surface Ozone Concentration in Campo Grande (MS)—Brazil Using Neural Networks, Natural Science, 7, 2015,171-178p.
  • EUROPEAN CLIMATE FOUNDATION. Roadmap 2050: a practical guide to a prosperous, low-carbon Europe. European Climate Foundation, The Hague, Netherlands, 2010.
  • INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE. Special report on renewable energy sources and climate change mitigation, summary for policymakers. Cambridge University Press, Cambridge, 2011.
  • HANSEN, J; SATO, M; RUEDY. R. Radiative forcing and climate response. J Geophys Res, 102, 1997, 6831–6864p.
  • HOLBEN, B. N.; ECK, T. F.; SLUTSKER I.; TANRÉ, D.; BUIS; J. P.; SETZER, A.; VERMOTE, E.; REAGAN, J. A.; KAUFMAN, Y. J.; NAKAJIMA, T.; LAVENU, F.; JANKOWIAK, I.; SMIRNOV, A. AERONET – A federated instrument network and data arquive for aerosol characterization, Remote Sensing Environ. 66, 1998, 1-16p.
  • JACOBSON, M. Z.; DELUCCHI, M. A. Providing all global energy with wind, water, and solar power, Part I: technologies, energy resources, quantities and areas of infrastructure, and materials. Energy Policy, 39, 2011, 1154–1169p.
  • JACOBSON, M. Z.; ARCHER, C. L. Saturation wind power potential and its implications for wind energy. Proc Natl Acad Sci, 109, 2012, 15679–15684p.
  • KLOSTER, S.; DENTENER, F.; FEICHTER, J.; RAES, F.; VAN AARDENNE, J.; ROECKNER E. Influence of future air pollution mitigation strategies on total aerosol radiative forcing. Atmos Chem Phys, 8, 2008, 6405–6437p.
  • KLOSTER, S.; DENTENER, F.; FEICHTER, J.; RAES, F.; LOHMANN, U.; ROECKNER, E. GCM study of future climate response to aerosol pollution Reductions. Clim Dyn, 34, 2010, 1177–1194p.
  • KUDISH, A. I.; IANETZ, A. Analysis of the solar radiation data for Beer Sheva, Israel, and its environs. Solar Energy, v.48, n.2,1992, 97-106p.
  • LATORRE MRDO, CARDOSO MRA. Análise de séries temporais em epidemiologia: uma introdução sobre aspectos metodológicos. Rev. bras. epidemiol. 2001;4(3):145-152.
  • MONTOGOMERY, D. C.; PECK, E. A.; VINING, G. G. Introduction to linear regression analysis. Third edition, John Wiley & Sons, New York, USA. 2001.
  • MUZATHIK A. M. Photovoltaic Modules Operating Temperature Estimation Using a Simple Correlation. International Journal of Energy Engineering. Aug. 2014, Vol. 4 Iss. 4, p. 151-158.
  • PATT, A.; PFENNINGER, S.; LILLIESTAM. J. Vulnerability of solar energy infrastructure and output to climate change. Clim Change, 121, 2013, 93–102p.
  • PIRES J; MARTINS F; SOUSA S; ALVIM-FERRAZ M; PEREIRA M. Selection and validation of parameters in multiple linear and principal component regressions. Environmental Modelling & Software, 23(1), 2008, 50-55p.
  • RAES, F.; SEINFELD.J. H. New directions: climate change and air pollution abatement: a bumpy road. Atmos Environ, 43, 2009, 5132–5133p.
  • RICIERI, R. P. Modelos de estimativa e avaliação dos métodos de medida da radiação solar difusa. UNESP, Botucatu, 1998. 81 p. Tese (Doutorado) – Programa de Pós Graduação em Energia na Agricultura - Universidade Estadual Paulista, Faculdade de Ciências Agronômicas, Botucatu, 1998.
  • ROECKNER, E; BENGTSSON, L; FEICHTER, J; LELIEVELD, J; RODHE., H. Transient climate change simulations with a coupled atmosphere-ocean GCM including the tropospheric sulfur cycle. J Clim, 12,1999, 3004–3032p.
  • SCHAFER, J. S.; HOLBEN, B. N.; ECK, T. F.; YAMASOE, M. A.; ARTAXO, P. Atmospheric effects on insolation in the Brazilian Amazon: Observed modification of solar radiation by clouds and smoke and derived single scattering albedo of fire aerosols. Journal of Geophysical Research, v.107, 2002, n. D20, 8074p.
  • SCHAEFFER, R.; SZKLO, A. S.; DE LUCENA, A. F. P; BORBA, B. S. M. C; NOGUEIRA, L. P. P.; FLEMING, F. P. Energy sector vulnerability to climate change: a review. Energy, 38, 2012, 1–12p.
  • SOUZA, M. P. & ECHER, E. Lei de Beer aplicada na atmosfera terrestre. Revista Brasileira de Ensino de Física. Vol. 23, n.03, 2001, 276-283p.
  • SOUZA, A.; PAVÃO, H. G.; OLIVEIRA, A. P G. Modeling of ozone due to weather conditions. Revista Brasileira de Climatologia. Ano 9 – Vol. 12, JAN/JUL 2013, 8-21p
  • SOUZA, A.; ARISTONE, F.; FERRARI, L. F.; REIS, R. R. Modelling of the Photovoltaic Cell Temperature According to the Ambient Temperature, Wind Speed and Solar Irradiance. Revista Brasileira de Energia, v. 5, 2016, 504-518p.
  • SOUZA, A.; ARISTONE, F. Estudo da Eficiência Energética de Células Fotovoltaicas em Função da Radiação Solar no Centro-oeste Brasileiro. Interespaço: Revista de Geografia e Interdisciplinaridade, v. 2, 2017, 115 -128p.
  • TRINURUK, P.; SORAPIPATANA, C.; CHENVIDHYA D. Estimating operating cell temperature of BIPV modules in Thailand, Renewable Energy, vol. 34, no. 11, 2009, 2515-2523p.
  • TWOMEY, S. The influence of pollution on the shortwave albedo of clouds. J Atmos Sci, 34, 1977, 1149–1152p.
  • UNECA United Nations. Economic Commission for Africa. Integrating renewable energy and climate change policies: exploring policy options for Africa. Working paper no. 10. African Climate Policy Centre; 2011.
  • VERMOTE, E. F.; VERMEULEN, V. Atmospheric correction algorithm: spectral reflectances (Mod09). 1999. Disponível em: <http://modis.gsfc.nasa.gov/data/atbd/atbd_mod08.pdf>.
  • YAMASOE, M. A.; ARTAXO, P.; MIGUEL, A. H.; ALLEN, A. G. Chemical composition of aerosol particles from direct emissions of biomass burning in the Amazon Basin: water-soluble species and trace elements. Atmospheric Environment, v.34, 2000, 1.641-1.653p.
Fonte de datos: Dialnet